**2. Methods**

The literature on gu<sup>t</sup> microbiota, diseases associated with perturbation of the gu<sup>t</sup> microbiota and technologies used in gu<sup>t</sup> microbiome research were searched through Google Scholar and PubMed/MEDLINE. The final search date was 29 February, 2020. Search strings such as "gut microbiome", "gastrointestinal microbiota", "microbiota dysbiosis and metabolic syndrome" and "technologies in microbiota research" were used. The search comprised original and review articles written in English. Retrieved articles were reviewed and sorted to eliminate duplicates and unwanted articles.

#### **3. Results and Discussion**

From the early start scientists used traditional culture and isolation techniques to study the flora of the body but today, improved methods including high-throughput culturing methods, high-throughput sequencing, microfluidics, human fecal transplant (Figure 1) approaches are being used in the study and treatment of the human microbiome ecosystem, so as to examine their role in inducing disease and to map out remedy against infective bacteria [16–19].

**Figure 1.** Various technologies used in the study of gastrointestinal microbiome. HTTP: high-throughput, FMT: fecal microbiota transplantation.

#### *3.1. The Human Gut and Its Microbiota*

Prior to its birth, it is presumed that the unborn is free of microbial flora, and that at birth, the infant first comes in contact with the resident microbial flora of the mothers' vagina if birth was through the natural birth canal, or the microbial flora of the mothers' skin if birth was through cesarean section [20–22]. Although some studies [23–25] have suggested the early inoculation of the fetus with bacteria and bacteria DNA through the placenta. The study by de Go ffau et al. [26] reported that the human placenta has no microbiome. Detected bacteria were acquired during labor and delivery. After birth, according to the findings of Koenig et al. [27], there were apparent chaotic shifts of microbiome from that endowed with genes facilitating lactate utilization and plant polysaccharide metabolism mediated by milk-based diet to increase in *Bacteroidetes* initiated by introduction of solid food that prepares the infant gu<sup>t</sup> for adult diet. However, in the findings of Di fferding et al. [28], the early introduction of infants to complementary food was associated with altered gu<sup>t</sup> microbiota composition and butyric acid concentration, which have been previously identified as precursors to oxidative stress, immune disorder and obesity in childhood.

The microbiome of the adult gu<sup>t</sup> accommodates various communities of phylotypes belonging to the phyla *Actinobacteria*, *Proteobacteria*, *Bacteroidetes*, *Fusobacteria*, *Firmicutes* and *Verrucomicrobia* [2]. Most of these phyla are present in the stomach, small intestine and colon. However, the colon is more populated with several genera belonging to the afore mentioned phyla, including the genus *Akkemansia*

that belongs to the phylum *Verrucomicrobia*, which has been found to be limited in patients with obesity, inflammatory bowel disease and other metabolic syndromes, while it is in abundance in the biopsies of healthy individuals [2,29]. As has been reported in several studies, dietary types and pattern shapes and determines the diversity of the gu<sup>t</sup> microbiome. In the submission of Amabebe et al. [30], high fat and carbohydrate diet builds a gu<sup>t</sup> microbiota that is predominated by *Methanobrevibacter*, *Firmicutes* (*Clostridium*) and *Prevotella* and deficient in bacteria such as *Bacteroides*, *Lactobacillus*, *Akkermansia* and *Bifidobacterium*. Barone et al. [31], in their study brought to the fore the impact of modern Paleolithic diet (MPD) that consist of vegetables, seeds, lean meat, fruits, eggs, nuts and fish on the gu<sup>t</sup> microbiome. They observed that the gu<sup>t</sup> microbiome of urban Italians adhering to MPD showed an ample degree of biodiversity with high relative abundance of fat-loving and bile tolerant microorganisms. As have been mentioned earlier, perturbations or dysbiosis in combination with altered permeability are crucial mechanisms that mediate disease manifestation [32]. Fecal microbiota transplantation (FMT) has gained relevance in recent times in the treatment and correction of gu<sup>t</sup> infections or disorders that might have resulted from the depletion of resident microbiota and infection by pathogenic bacteria. Huge successes have been recorded in FMT therapy, with about 92% e fficacy reported in the treatment of recurrent *Clostridium di*ffi*cile* infection [33]. In a recent study by Zou et al. [34], it was shown that patients with Crohn's disease and ulcerative colitis that had FMT were in remission after three days of transplant with notable bacterial colonization of the gut. FMT therapy has been extended to the treatment of lifestyle and other diseases, such as diabetes, metabolic syndrome, Parkinson's disease, obesity and cancer. FMT entails transfer of gu<sup>t</sup> microbiota in feces of a healthy donor to recipient patient to correct/treat a disorder or gastrointestinal disease [35–37]. Although the level of success of this procedure, is ye<sup>t</sup> to be wide spread due to some constraints identified by Cammarota et al. [38], including di fficulties with donor recruitment, lack of dedicated centers and issues pertaining to safety monitoring and regulation, hence, the proposal for the provision of stool banks to bridge the gap of FMT in clinical practice.

The afore mentioned technique o ffers a natural option to routine medical treatments of chronic ailments by providing direct and e ffective remedy preventing dysbiosis in the host, thereby improving health conditions [39,40].

#### *3.2. Technologies in Gastrointestinal Microbiome Study*

Since the structure, composition and diversity of the human gu<sup>t</sup> microbiota has been correlated with the health status of humans, it could be presumed that the future of combating certain ailments is through exploring individualized gastrointestinal microbiome as the gastrointestinal microbiome era heralds. In the past, scientists have used culture independent techniques such as electrophoresis based methods, including denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE) and PCR based methods, such as terminal restriction fragment length polymorphism (T-RFLP) and random amplified polymorphic DNA (RAPD), to study the community structure, diversity and genetic relatedness of bacteria in communities. Fluorescence in situ hybridization (FISH) is a cytogenetic technique that has been used in the study of individual microbes within gu<sup>t</sup> microbiota, such as *Listeria monocytogenes*, *Salmonella* species, *Helicobacter pylori* and *Yersinia enterocoliticai*, which are gu<sup>t</sup> pathogens [41–44]. Russmann et al. [45] used FISH in the diagnosis of *Helicobacter pylori* cultured isolates, and the same technique was used to pro ffer antibiotic treatment options. These methods had a lot of drawbacks, including the need for specific probes, low resolution, specificity and sensitivity. However, advances in sequencing and culture technologies have paved the way to analyzing big data arising from exploration of the rich microbiome ecosystem of the gut, which is evident in several studies, as shown in Table 2. Such technologies are high-throughput sequencing, microfluidics, high-throughput metabolomics, assays engineered organoids derived from human stem cells and high-throughput culturing [46]. They have far reaching advantages over the older or traditional technology already mentioned, but with some limitations as well (summary in Table 3). The pros and cons of these technologies are described below.




*J. Clin. Med.* **2020**, *9*,

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#### *3.3. 16S rRNA Gene Amplicon Sequencing*

The in-depth study of the gu<sup>t</sup> microbiome has been made possible through metagenomic approaches employing high-throughput sequencing technologies. Metagenomics entails the sequencing of total community DNA, which provides information on the richness, community structure and function of microbial species to be evaluated [54]. Sequencing of the hypervariable region of the 16S rRNA gene in combination with bioinformatics has been widely used to decipher the microbial composition of a community in an ecosystem like the gut. Using 16S rDNA illumina sequencing, Pires et al. [4] were able to characterize the gu<sup>t</sup> microbiome of individuals living in the Amazon, which revealed huge variation in composition, compared to people living in industrialized settings. Similarly, Barone et al. [31] used information from 16S rRNA gene sequencing to explain gu<sup>t</sup> microbiome response to a modern Paleolithic diet in a Western lifestyle context. Previous studies have also accessed and studied pediatric gu<sup>t</sup> microbiome using 454 pyrosequencing of *16S rRNA* genes [27,55]. The use of 16S rRNA sequencing in evaluating the microbial composition of a microbiota has its various imperfections which whole genome shotgun sequencing (WGSS) has taken care of. WGSS has been used in several gastrointestinal microbiome studies. Vogtmann et al. [56] reported the reproducibility using WGSS in the study of the association of colorectal cancer and the human gu<sup>t</sup> microbiome. Several bioinformatics platforms and tools, including Quantitative Insight Into Microbial Ecology (QIIME), Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt), STatistical Analyses of Metagenomic Profiles (STAMP) [51], Linear Discriminant Analysis with E ffect Size (LEfSe) [12] CLAssifier based on Reduced k-mers (CLARK), Mothur, Kraken [57] to mention a few that exist for analyzing the enormous genetic data that is generated from gastrointestinal microbiome studies. These tools help in predicting/assigning microbial taxonomy and give insight into the diversity, richness and composition of microbial species in a microbiota [58]. The enormous data obtained from metagenomic study of gu<sup>t</sup> microbiota can be employed by clinicians for proper diagnosis or prediction of gastrointestinal diseases and guide antibiotic therapy in clinical settings. Vila et al. [6], demonstrated through analyzing metagenomic data of the gu<sup>t</sup> microbiota of patients that IBD could be di fferentiated from IBS with microbial taxonomic makers, since both conditions have overlapping clinical manifestation that requires colonoscopy (an invasive procedure) for an accurate diagnosis by a clinician. Furthermore, in the same study, they were able to capture, from the same data, the resistome of the patients. A major limitation of this approach is the bias in the composition of databases to which comparisons are made.
